In Benedikt Lowe, Wolfgang Malzkorn & Thoralf Räsch (eds.), Foundations of The Formal Sciences II. Applications of Mathematical Logic in Philosophy and Linguistics [Trends in Logic]. Kluwer Academic Publishers. pp. 39-46 (2002)

Stephan Hartmann
Ludwig Maximilians Universität, München
Luc Bovens
University of North Carolina, Chapel Hill
There is a long philosophical tradition of addressing questions in philosophy of science and epistemology by means of the tools of Bayesian probability theory (see Earman (1992) and Howson and Urbach (1993)). In the late '70s, an axiomatic approach to conditional independence was developed within a Bayesian framework. This approach in conjunction with developments in graph theory are the two pillars of the theory of Bayesian Networks, which is a theory of probabilistic reasoning in artificial intelligence. The theory has been very successful over the last two decades and has found a wide array of applications ranging from medical diagnosis to safety systems for hazardous industries.
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